results_3

This model is a fine-tuned version of abhi317/results_2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1557

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 200

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	1	2.4711
No log	2.0	2	2.3635
No log	3.0	3	2.2591
No log	4.0	4	2.1869
No log	5.0	5	2.1121
No log	6.0	6	2.0433
No log	7.0	7	1.9845
No log	8.0	8	1.9252
No log	9.0	9	1.8642
No log	10.0	10	1.8104
No log	11.0	11	1.7649
No log	12.0	12	1.7260
No log	13.0	13	1.6873
No log	14.0	14	1.6532
No log	15.0	15	1.6242
No log	16.0	16	1.6066
No log	17.0	17	1.5801
No log	18.0	18	1.5596
No log	19.0	19	1.5346
No log	20.0	20	1.5040
No log	21.0	21	1.4759
No log	22.0	22	1.4507
No log	23.0	23	1.4294
No log	24.0	24	1.4083
No log	25.0	25	1.4008
No log	26.0	26	1.3787
No log	27.0	27	1.3444
No log	28.0	28	1.3196
No log	29.0	29	1.2965
No log	30.0	30	1.2714
No log	31.0	31	1.2447
No log	32.0	32	1.2207
No log	33.0	33	1.1911
No log	34.0	34	1.1596
No log	35.0	35	1.1291
No log	36.0	36	1.1054
No log	37.0	37	1.0787
No log	38.0	38	1.0492
No log	39.0	39	1.0278
No log	40.0	40	1.0058
No log	41.0	41	0.9850
No log	42.0	42	0.9644
No log	43.0	43	0.9525
No log	44.0	44	0.9405
No log	45.0	45	0.9255
No log	46.0	46	0.9018
No log	47.0	47	0.8715
No log	48.0	48	0.8439
No log	49.0	49	0.8271
No log	50.0	50	0.8079
No log	51.0	51	0.7844
No log	52.0	52	0.7619
No log	53.0	53	0.7389
No log	54.0	54	0.7216
No log	55.0	55	0.7085
No log	56.0	56	0.6971
No log	57.0	57	0.6864
No log	58.0	58	0.6771
No log	59.0	59	0.6650
No log	60.0	60	0.6552
No log	61.0	61	0.6451
No log	62.0	62	0.6375
No log	63.0	63	0.6317
No log	64.0	64	0.6252
No log	65.0	65	0.6179
No log	66.0	66	0.6081
No log	67.0	67	0.5980
No log	68.0	68	0.5844
No log	69.0	69	0.5751
No log	70.0	70	0.5651
No log	71.0	71	0.5603
No log	72.0	72	0.5540
No log	73.0	73	0.5442
No log	74.0	74	0.5342
No log	75.0	75	0.5228
No log	76.0	76	0.5093
No log	77.0	77	0.4987
No log	78.0	78	0.4859
No log	79.0	79	0.4728
No log	80.0	80	0.4602
No log	81.0	81	0.4523
No log	82.0	82	0.4444
No log	83.0	83	0.4349
No log	84.0	84	0.4250
No log	85.0	85	0.4154
No log	86.0	86	0.4078
No log	87.0	87	0.3995
No log	88.0	88	0.3929
No log	89.0	89	0.3863
No log	90.0	90	0.3796
No log	91.0	91	0.3737
No log	92.0	92	0.3663
No log	93.0	93	0.3624
No log	94.0	94	0.3592
No log	95.0	95	0.3537
No log	96.0	96	0.3467
No log	97.0	97	0.3424
No log	98.0	98	0.3381
No log	99.0	99	0.3332
No log	100.0	100	0.3276
No log	101.0	101	0.3245
No log	102.0	102	0.3208
No log	103.0	103	0.3170
No log	104.0	104	0.3148
No log	105.0	105	0.3132
No log	106.0	106	0.3106
No log	107.0	107	0.3086
No log	108.0	108	0.3053
No log	109.0	109	0.3038
No log	110.0	110	0.3020
No log	111.0	111	0.2998
No log	112.0	112	0.2966
No log	113.0	113	0.2931
No log	114.0	114	0.2887
No log	115.0	115	0.2838
No log	116.0	116	0.2785
No log	117.0	117	0.2735
No log	118.0	118	0.2688
No log	119.0	119	0.2644
No log	120.0	120	0.2624
No log	121.0	121	0.2610
No log	122.0	122	0.2593
No log	123.0	123	0.2564
No log	124.0	124	0.2537
No log	125.0	125	0.2506
No log	126.0	126	0.2465
No log	127.0	127	0.2441
No log	128.0	128	0.2408
No log	129.0	129	0.2380
No log	130.0	130	0.2348
No log	131.0	131	0.2313
No log	132.0	132	0.2277
No log	133.0	133	0.2238
No log	134.0	134	0.2197
No log	135.0	135	0.2155
No log	136.0	136	0.2118
No log	137.0	137	0.2090
No log	138.0	138	0.2067
No log	139.0	139	0.2044
No log	140.0	140	0.2020
No log	141.0	141	0.1995
No log	142.0	142	0.1970
No log	143.0	143	0.1950
No log	144.0	144	0.1929
No log	145.0	145	0.1906
No log	146.0	146	0.1884
No log	147.0	147	0.1876
No log	148.0	148	0.1868
No log	149.0	149	0.1860
No log	150.0	150	0.1851
No log	151.0	151	0.1838
No log	152.0	152	0.1829
No log	153.0	153	0.1818
No log	154.0	154	0.1811
No log	155.0	155	0.1810
No log	156.0	156	0.1802
No log	157.0	157	0.1791
No log	158.0	158	0.1777
No log	159.0	159	0.1763
No log	160.0	160	0.1748
No log	161.0	161	0.1739
No log	162.0	162	0.1726
No log	163.0	163	0.1716
No log	164.0	164	0.1710
No log	165.0	165	0.1702
No log	166.0	166	0.1694
No log	167.0	167	0.1693
No log	168.0	168	0.1688
No log	169.0	169	0.1680
No log	170.0	170	0.1669
No log	171.0	171	0.1661
No log	172.0	172	0.1655
No log	173.0	173	0.1649
No log	174.0	174	0.1647
No log	175.0	175	0.1644
No log	176.0	176	0.1643
No log	177.0	177	0.1639
No log	178.0	178	0.1634
No log	179.0	179	0.1628
No log	180.0	180	0.1622
No log	181.0	181	0.1616
No log	182.0	182	0.1610
No log	183.0	183	0.1605
No log	184.0	184	0.1598
No log	185.0	185	0.1593
No log	186.0	186	0.1589
No log	187.0	187	0.1584
No log	188.0	188	0.1581
No log	189.0	189	0.1578
No log	190.0	190	0.1576
No log	191.0	191	0.1573
No log	192.0	192	0.1571
No log	193.0	193	0.1568
No log	194.0	194	0.1565
No log	195.0	195	0.1563
No log	196.0	196	0.1560
No log	197.0	197	0.1559
No log	198.0	198	0.1558
No log	199.0	199	0.1557
No log	200.0	200	0.1557

Framework versions

• Transformers 4.39.3
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.2